• DocumentCode
    725866
  • Title

    Mining Patterns of Unsatisfiable Constraints to Detect Infeasible Paths

  • Author

    Sun Ding ; Hee Beng Kuan Tan ; Lwin Khin Shar

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2015
  • fDate
    23-24 May 2015
  • Firstpage
    65
  • Lastpage
    69
  • Abstract
    Detection of infeasible paths is required in many areas including test coverage analysis, test case generation, security vulnerability analysis, etc. Existing approaches typically use static analysis coupled with symbolic evaluation, heuristics, or path-pattern analysis. This paper is related to these approaches but with a different objective. It is to analyze code of real systems to build patterns of unsatisfiable constraints in infeasible paths. The resulting patterns can be used to detect infeasible paths without the use of constraint solver and evaluation of function calls involved, thus improving scalability. The patterns can be built gradually. Evaluation of the proposed approach shows promising results.
  • Keywords
    data mining; infeasible paths detection; pattern mining; unsatisfiable constraints; Accuracy; Pattern matching; Prototypes; Scalability; Software; Testing; Training; Infeasible paths; pattern mining; static analysis; structural testing; symbolic evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation of Software Test (AST), 2015 IEEE/ACM 10th International Workshop on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/AST.2015.21
  • Filename
    7166270